New Method Dramatically Improves Pathogen Detection

By Mark Dwortzan

Conceptual representation of H1N1 viruses captured by antibodies on the IRIS surface. (Image courtesy of Aysegul Yonet)
Conceptual representation of H1N1 viruses captured by antibodies on the IRIS surface. (Image courtesy of Aysegul Yonet)

Rapid, chip-scale, low-cost detection of viruses and other pathogens is of critical importance in curbing the spread of pandemics and responding to potential biowarfare agents, but today’s biosensor technology falls short in many ways. The most commonly used techniques, which rely on fluorescent labels, are expensive and cumbersome. Label-free biosensing devices avoid these drawbacks by using advanced photonics technology to identify potential pathogens, but they often lack sufficient sensitivity to detect nanoscale viral particles.

Presented in an article appearing in the October 19, 2010 edition of Nano Letters, a new, highly sensitive nanoparticle detection technique and device, developed by Professor  Selim Ünlü’s (ECE, BME, MSE) research group in collaboration with Professor  Bennett Goldberg (Physics, BME, ECE) and the MITRE Corporation, promises to overcome these challenges and pinpoint single virus and other pathogen particles with unprecedented speed, accuracy and affordability. Known as the Interferometric Reflectance Imaging Sensor (IRIS), the prototype device is the first not only to provide high-throughput detection of single nanoparticles of interest, but also to measure their size—an important factor in confirming the identity of a suspected pathogen.

In this study, IRIS detected and sized hundreds of individual H1N1 viruses. The research team, which also includes PhD students George Daaboul and Xirui Zhang (both BME) and Abdulkadir Yurt (MSE), described the system and the experiment in the Nano Letters article.

“Effective, label-free virus detection has been a major problem for decades, and I claim that IRIS presents a credible solution,” said Ünlü. “Compared to existing label-free techniques, our method is more robust, less expensive, and provides higher sensitivity and size verification.”

To detect and size pathogens, IRIS shines light from multi-color LED sources sequentially on nanoparticles bound to the sensor surface, which consists of a silicon dioxide layer atop a silicon substrate. Interference of light reflected from the sensor surface is modified by the presence of particles, producing a distinct signal that reveals the size of each particle. The device has a very large surface area and can capture the telltale interferometric responses, in parallel, of up to a million nanoparticles.

Because the sensor discriminates according to particle size, it can “weed out” noise from many smaller particles in the target solution that may bind to the sensor indiscriminately.

“The key criteria for any detector are sensitivity (how low a concentration can you use) and specificity (in the presence of other molecules, pathogens or cells, how sure are you that you detected the presence of the targeted pathogen amid other clutter or noise),” Ünlü explained. “You want an alarm that’s very sensitive, but that only goes off when there’s a fire.”

The research team next plans to augment IRIS with optical elements that will enable the device to recognize not only the size of potential pathogens, but also their shape and orientation. Their work is partially funded by Army Research Laboratories, the Smart Lighting Engineering Research Center and the MITRE Corporation.

UPDATE (September 16, 2014): Continuing their efforts on virus detection, the team now collaborates with Associate Professor John Connor (MED) and the University of Texas Medical Branch on detection of hemorrhagic fever diseases including Ebola and Marburg. They are also pursuing prototyping and commercialization efforts through NexGen Arrays. Current funding includes grants from the National Science Foundation and National Institutes of Health.


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